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Scatter matrix of numeric columns

You've investigated the new farmer's market data, and it's rather wide – with lots of columns of information for each market's row. Rather than painstakingly going through every combination of numeric columns and making a scatter plot to look at correlations, you decide to make a scatter matrix using the pandas built-in function.

Increasing the figure size with the figsize argument will help give the dense visualization some breathing room. Since there will be a lot of overlap for the points, decreasing the point opacity will help show the density of these overlaps.

Bu egzersiz

Improving Your Data Visualizations in Python

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Egzersiz talimatları

  • Subset the columns of the markets DataFrame to numeric_columns so the scatter matrix only shows numeric non-binary columns.
  • Increase figure size to 15 by 10 to avoid crowding.
  • Reduce point opacity to 50% to show regions of overlap.

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# Select just the numeric columns (exluding individual goods)
numeric_columns = ['lat', 'lon', 'months_open', 'num_items_sold', 'state_pop']

# Make a scatter matrix of numeric columns
pd.plotting.scatter_matrix(markets[____], 
                             # Make figure large to show details
                             figsize = ____, 
                           # Lower point opacity to show overlap
                           alpha = ____)

plt.show()
Kodu Düzenle ve Çalıştır